• Steven Ponce
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  • Steps to Create this Graphic
    • 1. Load Packages & Setup
    • 2. Read in the Data
    • 3. Examine the Data
    • 4. Tidy Data
    • 5. Visualization Parameters
    • 6. Plot
    • 7. Save
    • 8. Session Info
    • 9. GitHub Repository
    • 10. References
    • 11. Custom Functions Documentation

Finals Week Concentrates Medal Events Into Evening Hours

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Comparing opening days vs. closing days of the Milan-Cortina 2026 Olympics

TidyTuesday
Data Visualization
R Programming
2026
Comparing opening versus closing days of the Milan-Cortina 2026 Winter Olympics reveals how finals week dramatically concentrates medal events into evening hours, transforming the schedule from scattered daytime competition to evening-focused spectacle.
Author

Steven Ponce

Published

February 9, 2026

Figure 1: Grouped bar chart comparing medal event share by hour between Opening Days (gray bars) and Finals Week (teal bars) of the 2026 Winter Olympics. Finals Week shows dramatically higher medal event concentration in evening hours, with 4pm, 5pm, and 10pm reaching 100% medal events, while Opening Days shows lower, more scattered distribution throughout the day.

Steps to Create this Graphic

1. Load Packages & Setup

Show code
```{r}
#| label: load
#| warning: false
#| message: false
#| results: "hide"

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse, ggtext, showtext, janitor, 
    scales, glue
)
})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 10,
  height = 7,
  units  = "in",
  dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

2. Read in the Data

Show code
```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false

# tt <- tidytuesdayR::tt_load(2026, week = 06)
# schedule <- tt$schedule |> clean_names()
# rm(tt)
schedule <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-02-10/schedule.csv')
```

3. Examine the Data

Show code
```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(schedule)
```

4. Tidy Data

Show code
```{r}
#| label: tidy
#| warning: false

### |-  data cleaning ----
schedule_clean <- schedule |>
  mutate(
    olympic_day = as.numeric(date - min(date)) + 1,
    max_day = max(olympic_day),
    hour_local = hour(start_datetime_local),

    # Two periods for direct comparison
    period = case_when(
      olympic_day <= 3 ~ "Opening Days (1-3)",
      olympic_day >= max_day - 2 ~ "Finals Week",
      TRUE ~ NA_character_
    )
  ) |>
  filter(!is.na(period)) |>
  mutate(period = fct_relevel(period, "Opening Days (1-3)", "Finals Week"))

### |-  calculate medal event share ----
medal_share_comparison <- schedule_clean |>
  count(period, hour_local, is_medal_event) |>
  group_by(period, hour_local) |>
  mutate(
    total_events = sum(n),
    pct = n / total_events * 100
  ) |>
  ungroup() |>
  filter(is_medal_event == TRUE)
```

5. Visualization Parameters

Show code
```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = list(
      col_opening = "#CFCFCF",      
      col_closing = "#0d9488",       
      col_primetime_shade = "#ccfbf1",
      col_text_dark = "gray30"
  )
)

### |- titles and caption ----
title_text <- "Finals Week Concentrates Medal Events Into Evening Hours"

subtitle_text <- "Comparing opening days vs. closing days of the Milan-Cortina 2026 Olympics"

caption_text <- create_social_caption(
    tt_year = 2026,
    tt_week = 06,
    source_text = "2026 Winter Olympics Schedule (Milan-Cortina)"
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----
# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Text styling
    plot.title = element_text(
      face = "bold", family = fonts$title, size = rel(1.3),
      color = colors$title, margin = margin(b = 10), hjust = 0
    ),
    plot.subtitle = element_markdown(
      face = "italic", family = fonts$subtitle, lineheight = 1.2,
      color = colors$subtitle, size = rel(0.8), margin = margin(b = 20), hjust = 0
    ),

    # Grid
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.major = element_line(color = "gray90", linewidth = 0.25),

    # Axes
    axis.title = element_text(size = rel(0.8), color = "gray30"),
    axis.text = element_text(color = "gray30"),
    axis.text.y = element_text(size = rel(0.85)),
    axis.ticks = element_blank(),

    # Facets
    strip.background = element_rect(fill = "gray95", color = NA),
    strip.text = element_text(
      face = "bold",
      color = "gray20",
      size = rel(0.9),
      margin = margin(t = 6, b = 4)
    ),
    panel.spacing = unit(1.5, "lines"),

    # Legend elements
    legend.position = "plot",
    legend.title = element_text(
      family = fonts$subtitle,
      color = colors$text, size = rel(0.8), face = "bold"
    ),
    legend.text = element_text(
      family = fonts$tsubtitle,
      color = colors$text, size = rel(0.7)
    ),
    legend.margin = margin(t = 15),

    # Plot margin
    plot.margin = margin(10, 20, 10, 20),
    
  )
)

# Set theme
theme_set(weekly_theme)
```

6. Plot

Show code
```{r}
#| label: plot
#| warning: false

### |- final plot ----
p <- medal_share_comparison |>
  ggplot(aes(x = hour_local, y = pct, fill = period)) +

  # Geoms
  geom_col(
    aes(alpha = period),
    position = position_dodge(width = 0.9),
    width = 0.8
  ) +
  # Annotate
  annotate(
    "rect",
    xmin = 18, xmax = 22,
    ymin = 0, ymax = 100,
    fill = colors$palette$col_primetime_shade,
    alpha = 0.08
  ) +
  annotate(
    "text",
    x = 19.5, y = 90,
    label = "In finals week, evening schedules are\ndominated by medal events",
    family = fonts$text,
    size = 3.5,
    color = colors$palette$col_text_dark,
    lineheight = 1.1,
    hjust = 0.5
  ) +
  # Scales
  scale_fill_manual(
    values = c(
      "Opening Days (1-3)" = colors$palette$col_opening,
      "Finals Week" = colors$palette$col_closing
    )
  ) +
  scale_alpha_manual(
    values = c("Opening Days (1-3)" = 0.7, "Finals Week" = 0.95),
    guide = "none"
  ) +
  scale_x_continuous(
    breaks = seq(10, 22, 2),
    labels = function(x) paste0(x %% 12, ifelse(x < 12, "am", "pm")),
    expand = expansion(mult = c(0.02, 0.02))
  ) +
  scale_y_continuous(
    labels = function(x) paste0(x, "%"),
    limits = c(0, 100),
    expand = expansion(mult = c(0, 0.05))
  ) +
  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    x = "Hour of Day (Local Milan-Cortina Time)",
    y = "Share of Scheduled Events\nThat Are Medal Events",
    caption = caption_text
  ) +
  # Theme
  theme(
    axis.title.y = element_text(
      angle = 0,
      vjust = 1.04,
      hjust = 0.5,
      margin = margin(r = -100)
    ),
    plot.title = element_markdown(
      size = rel(1.4),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      lineheight = 1.15,
      margin = margin(t = 0, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.8),
      family = fonts$subtitle,
      color = alpha(colors$subtitle, 0.88),
      lineheight = 1.5,
      margin = margin(t = 5, b = 25)
    ),
    plot.caption = element_markdown(
      size = rel(0.5),
      family = fonts$subtitle,
      color = colors$caption,
      hjust = 0,
      lineheight = 1.4,
      margin = margin(t = 20, b = 5)
    )
  )
```

7. Save

Show code
```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot(
  plot = p, 
  type = "tidytuesday", 
  year = 2026, 
  week = 06, 
  width  = 10,
  height = 7,
  )
```

8. Session Info

Expand for Session Info
R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] here_1.0.1      glue_1.8.0      scales_1.3.0    janitor_2.2.0  
 [5] showtext_0.9-7  showtextdb_3.0  sysfonts_0.8.9  ggtext_0.1.2   
 [9] lubridate_1.9.3 forcats_1.0.0   stringr_1.5.1   dplyr_1.1.4    
[13] purrr_1.0.2     readr_2.1.5     tidyr_1.3.1     tibble_3.2.1   
[17] ggplot2_3.5.1   tidyverse_2.0.0 pacman_0.5.1   

loaded via a namespace (and not attached):
 [1] gtable_0.3.6      xfun_0.49         htmlwidgets_1.6.4 tzdb_0.5.0       
 [5] vctrs_0.6.5       tools_4.4.0       generics_0.1.3    curl_6.0.0       
 [9] parallel_4.4.0    gifski_1.32.0-1   fansi_1.0.6       pkgconfig_2.0.3  
[13] lifecycle_1.0.4   farver_2.1.2      compiler_4.4.0    textshaping_0.4.0
[17] munsell_0.5.1     codetools_0.2-20  snakecase_0.11.1  htmltools_0.5.8.1
[21] yaml_2.3.10       pillar_1.9.0      crayon_1.5.3      camcorder_0.1.0  
[25] magick_2.8.5      commonmark_1.9.2  tidyselect_1.2.1  digest_0.6.37    
[29] stringi_1.8.4     labeling_0.4.3    rsvg_2.6.1        rprojroot_2.0.4  
[33] fastmap_1.2.0     grid_4.4.0        colorspace_2.1-1  cli_3.6.4        
[37] magrittr_2.0.3    utf8_1.2.4        withr_3.0.2       bit64_4.5.2      
[41] timechange_0.3.0  rmarkdown_2.29    bit_4.5.0         ragg_1.3.3       
[45] hms_1.1.3         evaluate_1.0.1    knitr_1.49        markdown_1.13    
[49] rlang_1.1.6       gridtext_0.1.5    Rcpp_1.0.13-1     xml2_1.3.6       
[53] renv_1.0.3        svglite_2.1.3     rstudioapi_0.17.1 vroom_1.6.5      
[57] jsonlite_1.8.9    R6_2.5.1          systemfonts_1.1.0

9. GitHub Repository

Expand for GitHub Repo

The complete code for this analysis is available in tt_2026_06.qmd.

For the full repository, click here.

10. References

Expand for References
  1. Data Source:
    • TidyTuesday 2026 Week 06: 2026 Winter Olympics!

11. Custom Functions Documentation

📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

Functions Used:

  • fonts.R: setup_fonts(), get_font_families() - Font management with showtext
  • social_icons.R: create_social_caption() - Generates formatted social media captions
  • image_utils.R: save_plot() - Consistent plot saving with naming conventions
  • base_theme.R: create_base_theme(), extend_weekly_theme(), get_theme_colors() - Custom ggplot2 themes

Why custom functions?
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

Source Code:
View all custom functions → GitHub: R/utils

Back to top

Citation

BibTeX citation:
@online{ponce2026,
  author = {Ponce, Steven},
  title = {Finals {Week} {Concentrates} {Medal} {Events} {Into}
    {Evening} {Hours}},
  date = {2026-02-09},
  url = {https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2026/tt_2026_06.html},
  langid = {en}
}
For attribution, please cite this work as:
Ponce, Steven. 2026. “Finals Week Concentrates Medal Events Into Evening Hours.” February 9, 2026. https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2026/tt_2026_06.html.
Source Code
---
title: "Finals Week Concentrates Medal Events Into Evening Hours"
subtitle: "Comparing opening days vs. closing days of the Milan-Cortina 2026 Olympics"
description: "Comparing opening versus closing days of the Milan-Cortina 2026 Winter Olympics reveals how finals week dramatically concentrates medal events into evening hours, transforming the schedule from scattered daytime competition to evening-focused spectacle."
date: "2026-02-09"
author:
  - name: "Steven Ponce"
    url: "https://stevenponce.netlify.app"
citation:
  url: "https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2026/tt_2026_06.html" 
categories: ["TidyTuesday", "Data Visualization", "R Programming", "2026"]
tags: [
  "Winter Olympics",
  "Sports Scheduling",
  "Event Planning",
  "Grouped Bar Chart",
  "Comparative Analysis",
  "ggplot2",
  "Milan-Cortina 2026",
  "Olympic Broadcasting"
]
image: "thumbnails/tt_2026_06.png"
format:
  html:
    toc: true
    toc-depth: 5
    code-link: true
    code-fold: true
    code-tools: true
    code-summary: "Show code"
    self-contained: true
    theme: 
      light: [flatly, assets/styling/custom_styles.scss]
      dark: [darkly, assets/styling/custom_styles_dark.scss]
editor_options: 
  chunk_output_type: inline
execute: 
  freeze: true                                    
  cache: true                                       
  error: false
  message: false
  warning: false
  eval: true
---

![Grouped bar chart comparing medal event share by hour between Opening Days (gray bars) and Finals Week (teal bars) of the 2026 Winter Olympics. Finals Week shows dramatically higher medal event concentration in evening hours, with 4pm, 5pm, and 10pm reaching 100% medal events, while Opening Days shows lower, more scattered distribution throughout the day.](tt_2026_06.png){#fig-1}

### [**Steps to Create this Graphic**]{.mark}

#### [1. Load Packages & Setup]{.smallcaps}

```{r}
#| label: load
#| warning: false
#| message: false      
#| results: "hide"     

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse, ggtext, showtext, janitor, 
    scales, glue
)
})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 10,
  height = 7,
  units  = "in",
  dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

#### [2. Read in the Data]{.smallcaps}

```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false

# tt <- tidytuesdayR::tt_load(2026, week = 06)
# schedule <- tt$schedule |> clean_names()
# rm(tt)
schedule <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-02-10/schedule.csv')

```

#### [3. Examine the Data]{.smallcaps}

```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(schedule)
```

#### [4. Tidy Data]{.smallcaps}

```{r}
#| label: tidy
#| warning: false

### |-  data cleaning ----
schedule_clean <- schedule |>
  mutate(
    olympic_day = as.numeric(date - min(date)) + 1,
    max_day = max(olympic_day),
    hour_local = hour(start_datetime_local),

    # Two periods for direct comparison
    period = case_when(
      olympic_day <= 3 ~ "Opening Days (1-3)",
      olympic_day >= max_day - 2 ~ "Finals Week",
      TRUE ~ NA_character_
    )
  ) |>
  filter(!is.na(period)) |>
  mutate(period = fct_relevel(period, "Opening Days (1-3)", "Finals Week"))

### |-  calculate medal event share ----
medal_share_comparison <- schedule_clean |>
  count(period, hour_local, is_medal_event) |>
  group_by(period, hour_local) |>
  mutate(
    total_events = sum(n),
    pct = n / total_events * 100
  ) |>
  ungroup() |>
  filter(is_medal_event == TRUE)
```

#### [5. Visualization Parameters]{.smallcaps}

```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = list(
      col_opening = "#CFCFCF",      
      col_closing = "#0d9488",       
      col_primetime_shade = "#ccfbf1",
      col_text_dark = "gray30"
  )
)

### |- titles and caption ----
title_text <- "Finals Week Concentrates Medal Events Into Evening Hours"

subtitle_text <- "Comparing opening days vs. closing days of the Milan-Cortina 2026 Olympics"

caption_text <- create_social_caption(
    tt_year = 2026,
    tt_week = 06,
    source_text = "2026 Winter Olympics Schedule (Milan-Cortina)"
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----
# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Text styling
    plot.title = element_text(
      face = "bold", family = fonts$title, size = rel(1.3),
      color = colors$title, margin = margin(b = 10), hjust = 0
    ),
    plot.subtitle = element_markdown(
      face = "italic", family = fonts$subtitle, lineheight = 1.2,
      color = colors$subtitle, size = rel(0.8), margin = margin(b = 20), hjust = 0
    ),

    # Grid
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.major = element_line(color = "gray90", linewidth = 0.25),

    # Axes
    axis.title = element_text(size = rel(0.8), color = "gray30"),
    axis.text = element_text(color = "gray30"),
    axis.text.y = element_text(size = rel(0.85)),
    axis.ticks = element_blank(),

    # Facets
    strip.background = element_rect(fill = "gray95", color = NA),
    strip.text = element_text(
      face = "bold",
      color = "gray20",
      size = rel(0.9),
      margin = margin(t = 6, b = 4)
    ),
    panel.spacing = unit(1.5, "lines"),

    # Legend elements
    legend.position = "plot",
    legend.title = element_text(
      family = fonts$subtitle,
      color = colors$text, size = rel(0.8), face = "bold"
    ),
    legend.text = element_text(
      family = fonts$tsubtitle,
      color = colors$text, size = rel(0.7)
    ),
    legend.margin = margin(t = 15),

    # Plot margin
    plot.margin = margin(10, 20, 10, 20),
    
  )
)

# Set theme
theme_set(weekly_theme)
```

#### [6. Plot]{.smallcaps}

```{r}
#| label: plot
#| warning: false

### |- final plot ----
p <- medal_share_comparison |>
  ggplot(aes(x = hour_local, y = pct, fill = period)) +

  # Geoms
  geom_col(
    aes(alpha = period),
    position = position_dodge(width = 0.9),
    width = 0.8
  ) +
  # Annotate
  annotate(
    "rect",
    xmin = 18, xmax = 22,
    ymin = 0, ymax = 100,
    fill = colors$palette$col_primetime_shade,
    alpha = 0.08
  ) +
  annotate(
    "text",
    x = 19.5, y = 90,
    label = "In finals week, evening schedules are\ndominated by medal events",
    family = fonts$text,
    size = 3.5,
    color = colors$palette$col_text_dark,
    lineheight = 1.1,
    hjust = 0.5
  ) +
  # Scales
  scale_fill_manual(
    values = c(
      "Opening Days (1-3)" = colors$palette$col_opening,
      "Finals Week" = colors$palette$col_closing
    )
  ) +
  scale_alpha_manual(
    values = c("Opening Days (1-3)" = 0.7, "Finals Week" = 0.95),
    guide = "none"
  ) +
  scale_x_continuous(
    breaks = seq(10, 22, 2),
    labels = function(x) paste0(x %% 12, ifelse(x < 12, "am", "pm")),
    expand = expansion(mult = c(0.02, 0.02))
  ) +
  scale_y_continuous(
    labels = function(x) paste0(x, "%"),
    limits = c(0, 100),
    expand = expansion(mult = c(0, 0.05))
  ) +
  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    x = "Hour of Day (Local Milan-Cortina Time)",
    y = "Share of Scheduled Events\nThat Are Medal Events",
    caption = caption_text
  ) +
  # Theme
  theme(
    axis.title.y = element_text(
      angle = 0,
      vjust = 1.04,
      hjust = 0.5,
      margin = margin(r = -100)
    ),
    plot.title = element_markdown(
      size = rel(1.4),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      lineheight = 1.15,
      margin = margin(t = 0, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.8),
      family = fonts$subtitle,
      color = alpha(colors$subtitle, 0.88),
      lineheight = 1.5,
      margin = margin(t = 5, b = 25)
    ),
    plot.caption = element_markdown(
      size = rel(0.5),
      family = fonts$subtitle,
      color = colors$caption,
      hjust = 0,
      lineheight = 1.4,
      margin = margin(t = 20, b = 5)
    )
  )
```

#### [7. Save]{.smallcaps}

```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot(
  plot = p, 
  type = "tidytuesday", 
  year = 2026, 
  week = 06, 
  width  = 10,
  height = 7,
  )
```

#### [8. Session Info]{.smallcaps}

::: {.callout-tip collapse="true"}
##### Expand for Session Info

```{r, echo = FALSE}
#| eval: true
#| warning: false

sessionInfo()
```
:::

#### [9. GitHub Repository]{.smallcaps}

::: {.callout-tip collapse="true"}
##### Expand for GitHub Repo

The complete code for this analysis is available in [`tt_2026_06.qmd`](https://github.com/poncest/personal-website/blob/master/data_visualizations/TidyTuesday/2026/tt_2026_06.qmd).

For the full repository, [click here](https://github.com/poncest/personal-website/).
:::

#### [10. References]{.smallcaps}

::: {.callout-tip collapse="true"}
##### Expand for References
1.  **Data Source:**
    -   TidyTuesday 2026 Week 06: [2026 Winter Olympics!](https://github.com/rfordatascience/tidytuesday/blob/main/data/2026/2026-02-10/readme.md)

:::


#### [11. Custom Functions Documentation]{.smallcaps}

::: {.callout-note collapse="true"}
##### 📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

**Functions Used:**

-   **`fonts.R`**: `setup_fonts()`, `get_font_families()` - Font management with showtext
-   **`social_icons.R`**: `create_social_caption()` - Generates formatted social media captions
-   **`image_utils.R`**: `save_plot()` - Consistent plot saving with naming conventions
-   **`base_theme.R`**: `create_base_theme()`, `extend_weekly_theme()`, `get_theme_colors()` - Custom ggplot2 themes

**Why custom functions?**\
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

**Source Code:**\
View all custom functions → [GitHub: R/utils](https://github.com/poncest/personal-website/tree/master/R)
:::

© 2024 Steven Ponce

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